OpenRaiser/Intern-Atlas huggingface dataset:
SAR Image Despeckling Algorithms using Stochastic Distances and Nonlocal Means
Venue: arXiv cs.IT 2013
Year: 2013

This paper presents two approaches for filter design based on stochastic distances for intensity speckle reduction. A window is defined around each pixel, overlapping samples are compared and only those which pass a goodness-of-fit test are used to compute the filtered value. The tests stem from stochastic divergences within the Information Theory framework. The technique is applied to intensity Synthetic Aperture Radar (SAR) data with homogeneous regions using the Gamma model. The first approach uses a Nagao-Matsuyama-type procedure for setting the overlapping samples, and the second uses the nonlocal method. The proposals are compared with the Improved Sigma filter and with anisotropic diffusion for speckled data (SRAD) using a protocol based on Monte Carlo simulation. Among the criteria used to quantify the quality of filters, we employ the equivalent number of looks, and line and edge preservation. Moreover, we also assessed the filters by the Universal Image Quality Index and by the Pearson correlation between edges. Applications to real images are also discussed. The proposed methods show good results.
Influences Combination of Multi-Sensor Images on Classification Accuracy
Venue: arXiv cs.CV 2013
Year: 2013

This paper focuses on two main issues; first one is the impact of combination of multi-sensor images on the supervised learning classification accuracy using segment Fusion (SF). The second issue attempts to undertake the study of supervised machine learning classification technique of remote sensing images by using four classifiers like Parallelepiped (Pp), Mahalanobis Distance (MD), Maximum-Likelihood (ML) and Euclidean Distance(ED) classifiers, and their accuracies have been evaluated on their respected classification to choose the best technique for classification of remote sensing images. QuickBird multispectral data (MS) and panchromatic data (PAN) have been used in this study to demonstrate the enhancement and accuracy assessment of fused image over the original images using ALwassaiProcess software. According to experimental result of this study, is that the test results indicate the supervised classification results of fusion image, which generated better than the MS did. As well as the result with Euclidean classifier is robust and provides better results than the other classifiers do, despite of the popular belief that the maximum-likelihood classifier is the most accurate classifier.
A study of retrieval algorithms of sparse messages in networks of neural cliques
Venue: arXiv cs.NE 2013
Year: 2013

Associative memories are data structures addressed using part of the content rather than an index. They offer good fault reliability and biological plausibility. Among different families of associative memories, sparse ones are known to offer the best efficiency (ratio of the amount of bits stored to that of bits used by the network itself). Their retrieval process performance has been shown to benefit from the use of iterations. However classical algorithms require having prior knowledge about the data to retrieve such as the number of nonzero symbols. We introduce several families of algorithms to enhance the retrieval process performance in recently proposed sparse associative memories based on binary neural networks. We show that these algorithms provide better performance, along with better plausibility than existing techniques. We also analyze the required number of iterations and derive corresponding curves.
On the Generative Power of Omega-Grammars and Omega-Automata
Venue: arXiv cs.FL 2013
Year: 2013

An ω-grammar is a formal grammar used to generate ω-words (i.e. infinite length words), while an ω-automaton is an automaton used to recognize ω-words. This paper gives clean and uniform definitions for ω-grammars and ω-automata, provides a systematic study of the generative power of ω-grammars with respect to ω-automata, and presents a complete set of results for various types of ω-grammars and acceptance modes. We use the tuple (σ,ρ,π) to denote various acceptance modes, where σdenotes that some designated elements should appear at least once or infinitely often, ρdenotes some binary relation between two sets, and πdenotes normal or leftmost derivations. Technically, we propose (σ,ρ,π)-accepting ω-grammars, and systematically study their relative generative power with respect to (σ,ρ)-accepting ω-automata. We show how to construct some special forms of ω-grammars, such as ε-production-free ω-grammars. We study the equivalence or inclusion relations between ω$-grammars and ω-automata by establishing the translation techniques. In particular, we show that, for some acceptance modes, the generative power of ω-CFG is strictly weaker than ω-PDA, and the generative power of ω-CSG is equal to ω-TM (rather than linear-bounded ω-automata-like devices). Furthermore, we raise some remaining open problems for two of the acceptance modes.
Topological security assessment of technological networks
Venue: arXiv cs.SI 2013
Year: 2013

The spreading of dangerous malware or faults in inter-dependent networks of electronics devices has raised deep concern, because from the ICT networks infections may propagate to other Critical Infrastructures producing the well-known domino or cascading effect. Researchers are attempting to develop a high level analysis of malware propagation discarding software details, in order to generalize to the maximum extent the defensive strategies. For example, it has been suggested that the maximum eigenvalue of the network adjacency matrix could act as a threshold for the malware's spreading. This leads naturally to use the spectral graph theory to identify the most critical and influential nodes in technological networks. Many well-known graph parameters have been studied in the past years to accomplish the task. Here we test our AV11 algorithm showing that outperforms degree, closeness, betweenness centrality and the dynamical importance
Ultra-low Energy, High-Performance Dynamic Resistive Threshold Logic
Venue: arXiv cs.ET 2013
Year: 2013

We propose dynamic resistive threshold-logic (DRTL) design based on non-volatile resistive memory. A threshold logic gate (TLG) performs summation of multiple inputs multiplied by a fixed set of weights and compares the sum with a threshold. DRTL employs resistive memory elements to implement the weights and the thresholds, while a compact dynamic CMOS latch is used for the comparison operation. The resulting DRTL gate acts as a low-power, configurable dynamic logic unit and can be used to build fully pipelined, high-performance programmable computing blocks. Multiple stages in such a DRTL design can be connected using energy-efficient low swing programmable interconnect networks based on resistive switches. Owing to memory-based compact logic and interconnect design and highspeed dynamic-pipelined operation, DRTL can achieve more than two orders of magnitude improvement in energy-delay product as compared to look-up table based CMOS FPGA.
Synthesizing Multiple Boolean Functions using Interpolation on a Single Proof
Venue: arXiv cs.LO 2013
Year: 2013

It is often difficult to correctly implement a Boolean controller for a complex system, especially when concurrency is involved. Yet, it may be easy to formally specify a controller. For instance, for a pipelined processor it suffices to state that the visible behavior of the pipelined system should be identical to a non-pipelined reference system (Burch-Dill paradigm). We present a novel procedure to efficiently synthesize multiple Boolean control signals from a specification given as a quantified first-order formula (with a specific quantifier structure). Our approach uses uninterpreted functions to abstract details of the design. We construct an unsatisfiable SMT formula from the given specification. Then, from just one proof of unsatisfiability, we use a variant of Craig interpolation to compute multiple coordinated interpolants that implement the Boolean control signals. Our method avoids iterative learning and back-substitution of the control functions. We applied our approach to synthesize a controller for a simple two-stage pipelined processor, and present first experimental results.
Bit Rate of Programs
Venue: arXiv cs.SE 2013
Year: 2013

A program can be considered as a device that generates discrete time signals, where a signal is an execution. Shannon information rate, or bit rate, of the signals may not be uniformly distributed. When the program is specified by a finite state transition system, algorithms are provided in identifying information-rich components. For a black-box program that has a partial specification or does not even have a specification, a bit rate signal and its spectrum are studied, which make use of data compression and the Fourier transform. The signal provides a bit-rate coverage for testing the black-box while its spectrum indicates a visual representation for execution's information characteristics.
A secured communication link design using narrow line of sight technique
Venue: arXiv cs.NI 2013
Year: 2013

In recent wireless networking optical communication is an emerging field. Another novel approach of optical communication using Narrow Line of Sight technique is discussed. Array of trans receivers are placed on the ceiling to communicate with the mobile nodes (users / trans receivers) instead of a single transmitter. An intelligent position tracking technique based on the informations available from prepositioned sensors and using them in simple geometric equations is described. Intelligent cell concept is used to facilitate the tracking system. The whole wide area is divided into several sub areas and some of the sub areas are designated as boundary sub areas which hold the data regarding the movement of the mobile nodes. The Diffie Hellman simple authenticated key agreement is used for secure communication.
E-learning Services for Rural Communities
Venue: arXiv cs.CY 2013
Year: 2013

Information and communication technologies brought-in tools and techniques in the field of education that introduced new concepts of teaching and learning. Learning management system is one of the key tools used in educational institutes to facilitate e-learning. There is remarkable digital divide among urban and rural areas. In this paper, we present a model for providing e-learning services to remote/rural areas in order to promote and facilitate modern education. A dedicated resource center, hosting the learning management system, facilitates e-learning centers through Internet. The overall goal of this model is to have a cost-effective learning environment equipped with latest technologies to provide learners an opportunity to get insight into new information and communication technologies and e-learning environment. The model offers new teaching methodology with enhance utilization of learning management system in teaching and learning. Basic characteristics and technical aspects will be considered as well. The study will also promote development and usage of open-source technologies.
A Research Framework for the Clean-Slate Design of Next-Generation Optical Access
Venue: arXiv cs.NI 2013
Year: 2013

A comprehensive research framework for a comparative analysis of candidate network architectures and protocols in the clean-slate design of next-generation optical access is proposed. The proposed research framework consists of a comparative analysis framework based on multivariate non-inferiority testing and a notion of equivalent circuit rate taking into account user-perceived performances, and a virtual test bed providing a complete experimental platform for the comparative analysis. The capability of the research framework is demonstrated through numerical results from the study of the elasticity of hybrid TDM/WDM-PON based on tunable transceivers.
A review on handwritten character and numeral recognition for Roman, Arabic, Chinese and Indian scripts
Venue: arXiv cs.CV 2013
Year: 2013

There are a lot of intensive researches on handwritten character recognition (HCR) for almost past four decades. The research has been done on some of popular scripts such as Roman, Arabic, Chinese and Indian. In this paper we present a review on HCR work on the four popular scripts. We have summarized most of the published paper from 2005 to recent and also analyzed the various methods in creating a robust HCR system. We also added some future direction of research on HCR.
David Poole's Specificity Revised
Venue: arXiv cs.AI 2013
Year: 2013

In the middle of the 1980s, David Poole introduced a semantical, model-theoretic notion of specificity to the artificial-intelligence community. Since then it has found further applications in non-monotonic reasoning, in particular in defeasible reasoning. Poole tried to approximate the intuitive human concept of specificity, which seems to be essential for reasoning in everyday life with its partial and inconsistent information. His notion, however, turns out to be intricate and problematic, which --- as we show --- can be overcome to some extent by a closer approximation of the intuitive human concept of specificity. Besides the intuitive advantages of our novel specificity ordering over Poole's specificity relation in the classical examples of the literature, we also report some hard mathematical facts: Contrary to what was claimed before, we show that Poole's relation is not transitive. The present means to decide our novel specificity relation, however, show only a slight improvement over the known ones for Poole's relation, and further work is needed in this aspect.
The Simple Rules of Social Contagion
Venue: arXiv cs.SI 2013
Year: 2013

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is significantly more complex than the prediction of the pathogen model. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of the exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We apply our model to real-time forecasting of user behavior.
Computing Equilibria of Semi-algebraic Economies Using Triangular Decomposition and Real Solution Classification
Venue: arXiv cs.SC 2013
Year: 2013

In this paper, we are concerned with the problem of determining the existence of multiple equilibria in economic models. We propose a general and complete approach for identifying multiplicities of equilibria in semi-algebraic economies, which may be expressed as semi-algebraic systems. The approach is based on triangular decomposition and real solution classification, two powerful tools of algebraic computation. Its effectiveness is illustrated by two examples of application.
Group-Sparse Signal Denoising: Non-Convex Regularization, Convex Optimization
Venue: arXiv cs.CV 2013
Year: 2013

Convex optimization with sparsity-promoting convex regularization is a standard approach for estimating sparse signals in noise. In order to promote sparsity more strongly than convex regularization, it is also standard practice to employ non-convex optimization. In this paper, we take a third approach. We utilize a non-convex regularization term chosen such that the total cost function (consisting of data consistency and regularization terms) is convex. Therefore, sparsity is more strongly promoted than in the standard convex formulation, but without sacrificing the attractive aspects of convex optimization (unique minimum, robust algorithms, etc.). We use this idea to improve the recently developed 'overlapping group shrinkage' (OGS) algorithm for the denoising of group-sparse signals. The algorithm is applied to the problem of speech enhancement with favorable results in terms of both SNR and perceptual quality.
Discovering Latent Patterns from the Analysis of User-Curated Movie Lists
Venue: arXiv cs.SI 2013
Year: 2013

User content curation is becoming an important source of preference data, as well as providing information regarding the items being curated. One popular approach involves the creation of lists. On Twitter, these lists might contain accounts relevant to a particular topic, whereas on a community site such as the Internet Movie Database (IMDb), this might take the form of lists of movies sharing common characteristics. While list curation involves substantial combined effort on the part of users, researchers have rarely looked at mining the outputs of this kind of crowdsourcing activity. Here we study a large collection of movie lists from IMDb. We apply network analysis methods to a graph that reflects the degree to which pairs of movies are "co-listed", that is, assigned to the same lists. This allows us to uncover a more nuanced grouping of movies that goes beyond categorisation schemes based on attributes such as genre or director.
Artificial Immune Systems (INTROS 2)
Venue: arXiv cs.NE 2013
Year: 2013

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self or non-self substances. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune system have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.
Is Somebody Watching Your Facebook Newsfeed?
Venue: arXiv cs.SI 2013
Year: 2013

With the popularity of Social Networking Services (SNS), more and more sensitive information are stored online and associated with SNS accounts. The obvious value of SNS accounts motivates the usage stealing problem -- unauthorized, stealthy use of SNS accounts on the devices owned/used by account owners without any technology hacks. For example, anxious parents may use their kids' SNS accounts to inspect the kids' social status; husbands/wives may use their spouses' SNS accounts to spot possible affairs. Usage stealing could happen anywhere in any form, and seriously invades the privacy of account owners. However, there is no any currently known defense against such usage stealing. To an SNS operator (e.g., Facebook Inc.), usage stealing is hard to detect using traditional methods because such attackers come from the same IP addresses/devices, use the same credentials, and share the same accounts as the owners do. In this paper, we propose a novel continuous authentication approach that analyzes user browsing behavior to detect SNS usage stealing incidents. We use Facebook as a case study and show that it is possible to detect such incidents by analyzing SNS browsing behavior. Our experiment results show that our proposal can achieve higher than 80% detection accuracy within 2 minutes, and higher than 90% detection accuracy after 7 minutes of observation time.
On Computability of Equilibria in Markets with Production
Venue: arXiv cs.GT 2013
Year: 2013

Although production is an integral part of the Arrow-Debreu market model, most of the work in theoretical computer science has so far concentrated on markets without production, i.e., the exchange economy. This paper takes a significant step towards understanding computational aspects of markets with production. We first define the notion of separable, piecewise-linear concave (SPLC) production by analogy with SPLC utility functions. We then obtain a linear complementarity problem (LCP) formulation that captures exactly the set of equilibria for Arrow-Debreu markets with SPLC utilities and SPLC production, and we give a complementary pivot algorithm for finding an equilibrium. This settles a question asked by Eaves in 1975 of extending his complementary pivot algorithm to markets with production. Since this is a path-following algorithm, we obtain a proof of membership of this problem in PPAD, using Todd, 1976. We also obtain an elementary proof of existence of equilibrium (i.e., without using a fixed point theorem), rationality, and oddness of the number of equilibria. We further give a proof of PPAD-hardness for this problem and also for its restriction to markets with linear utilities and SPLC production. Experiments show that our algorithm runs fast on randomly chosen examples, and unlike previous approaches, it does not suffer from issues of numerical instability. Additionally, it is strongly polynomial when the number of goods or the number of agents and firms is constant. This extends the result of Devanur and Kannan (2008) to markets with production. Finally, we show that an LCP-based approach cannot be extended to PLC (non-separable) production, by constructing an example which has only irrational equilibria.
Evolution Theory of Self-Evolving Autonomous Problem Solving Systems
Venue: arXiv cs.AI 2013
Year: 2013

The present study gives a mathematical framework for self-evolution within autonomous problem solving systems. Special attention is set on universal abstraction, thereof generation by net block homomorphism, consequently multiple order solving systems and the overall decidability of the set of the solutions. By overlapping presentation of nets new abstraction relation among nets is formulated alongside with consequent alphabetical net block renetting system proportional to normal forms of renetting systems regarding the operational power. A new structure in self-evolving problem solving is established via saturation by groups of equivalence relations and iterative closures of generated quotient transducer algebras over the whole evolution.
A Novel Method for Image Integrity Authentication Based on Fixed Point Theory
Venue: arXiv cs.CR 2013
Year: 2013

Based on fixed point theory, this paper proposes a simple but efficient method for image integrity authentication, which is different from Digital Signature and Fragile Watermarking. By this method, any given image can be transformed into a fixed point of a well-chosen function, which can be constructed with periodic functions. The authentication can be realized due to the fragility of the fixed points. The experiments show that 'Fixed Point Image' performs well in security, transparence, fragility and tampering localization.